GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects.
Deep learning based one class classification code targeting one class image classification. Tests carried out on Abnormal image detection, Novel image detection and Active Authentication reported state of the art results. - PramuPerera/DeepOneClass
The image dataset of the fully mechanized longwall mining face (DsLMF+) is of great significance for the application of object detection using intelligence data-mining in the field of coal mine, which is expected to be able to identify and warn the underground abnormal conditions, solving the ...
Our code is available at https://github.com/cl2227619761/TCT_Detection. Copyright 2021. Published by Elsevier B.V.doi:10.1016/j.media.2021.102197Lei CaoJinying YangZhiwei RongLulu LiYan HouMedical Image Analysis
Full size image Igf2enhancer loss affects dopamine levels and synapses We then examined transgenic mice carrying an intergenicIgf2enhancer deletion (Fig.3). Since the intergenic enhancer region we deleted in mice is near theIgf2gene but may not be the ortholog of the humanIGF2enhancer, we firs...
Real-time quantitative polymerase chain reaction (RT-qPCR) was performed using Power SYBR Green PCR Master Mix in a BioRad CFX96 thermocycler using the standard SyBR Green detection protocol as outlined by the manufacturer (Applied Biosystems). Briefly, 12 ng of total cDNA, 50nM (each) primer...
代码地址:https://github.com/AhmedImtiazPrio/heartnet 摘要:心音异常的自动检测在心脏病的早期诊断中,尤其是在低资源环境下,发挥着至关重要的作用。此任务的最新算法使用一组有限冲激响应(FIR)带通滤波器作为前端,然后使用卷积神经网络(CNN)模型。在这项工作中,我们提出了一种新的CNN结构,它使用时间卷积(tConv...
8.--noneclass : Number of classes to be considered for one-class testing. We used 40 for novelty detection. 6 for abnormal image detection. 9.--task : Specify oneclass task novelty/ abnormal 10.--niter : Number of training iterations ...
GitHub is where people build software. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects.
Run train.py to train the model Run test.py to test on testing data. Run start_live_feed.py to test the model on live webcam feed. You can adjust the threshold parameter in test.py to different values to adjust sensitivity Datasets Recommended: Avenue Dataset for Anomaly DetectionAbout...